Weighted Bootstrap by Barbe Philippe (11 results)
Language: English
Published by Springer-Verlag, 1995
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Condition: Fair. This is an ex-library book and may have the usual library/used-book markings inside.This book has soft covers. In fair condition, suitable as a study copy. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,450grams, ISBN:9780387944784.
Language: English
Published by Springer, 1995
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Language: English
Published by Springer, 1995
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Condition: New. pp. 244.
Language: English
Published by Springer Verlag, 1995
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Language: English
Published by Springer, Springer, 1995
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - INTRODUCTION 1) Introduction In 1979, Efron introduced the bootstrap method as a kind of universal tool to obtain approximation of the distribution of statistics. The now well known underlying idea is the following : consider a sample X of Xl ' n i…ndependent and identically distributed H.i.d.) random variables (r. v,'s) with unknown probability measure (p.m.) P . Assume we are interested in approximating the distribution of a statistical functional T(P ) the -1 nn empirical counterpart of the functional T(P) , where P n := n l:i=l aX. is 1 the empirical p.m. Since in some sense P is close to P when n is large, n - - LLd. from P and builds the empirical p.m. if one samples Xl ' . , Xm n n -1 mn - - P T(P ) conditionally on := mn l: i =1 a - ' then the behaviour of P m n,m n n n X. 1 T(P ) should imitate that of when n and mn get large. n This idea has lead to considerable investigations to see when it is correct, and when it is not. When it is not, one looks if there is any way to adapt it.
Language: English
Published by Springer New York, 1995
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Condition: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | INTRODUCTION 1) Introduction In 1979, Efron introduced the bootstrap method as a kind of universal tool to obtain approximation of the distribution of statistics. The now well known underlying idea is the following : consider a sample X of Xl ' n i…ndependent and identically distributed H.i.d.) random variables (r. v,'s) with unknown probability measure (p.m.) P . Assume we are interested in approximating the distribution of a statistical functional T(P ) the -1 nn empirical counterpart of the functional T(P) , where P n := n l:i=l aX. is 1 the empirical p.m. Since in some sense P is close to P when n is large, n ¿ ¿ LLd. from P and builds the empirical p.m. if one samples Xl ' . , Xm n n -1 mn ¿ ¿ P T(P ) conditionally on := mn l: i =1 a ¿ ' then the behaviour of P m n,m n n n X. 1 T(P ) should imitate that of when n and mn get large. n This idea has lead to considerable investigations to see when it is correct, and when it is not. When it is not, one looks if there is any way to adapt it.
Language: English
Published by Springer, 1995
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Language: English
Published by Springer New York, 1995
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Kartoniert / Broschiert. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. INTRODUCTION 1) Introduction In 1979, Efron introduced the bootstrap method as a kind of universal tool to obtain approximation of the distribution of statistics. The now well known underlying… idea is the following : consider a sample X of Xl n independen.
Language: English
Published by Springer, 1995
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Condition: New. Print on Demand pp. 244 49:B&W 6.14 x 9.21 in or 234 x 156 mm (Royal 8vo) Perfect Bound on White w/Gloss Lam.
Language: English
Published by Springer, 1995
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Condition: New. PRINT ON DEMAND pp. 244.
Language: English
Published by Springer, Springer Feb 1995, 1995
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -INTRODUCTION 1) Introduction In 1979, Efron introduced the bootstrap method as a kind of universal tool to obtain approximation of the distribution of statistics. The now well known underlying idea is the following : consider a sample X… of Xl ' n independent and identically distributed H.i.d.) random variables (r. v,'s) with unknown probability measure (p.m.) P . Assume we are interested in approximating the distribution of a statistical functional T(P ) the -1 nn empirical counterpart of the functional T(P) , where P n := n l:i=l aX. is 1 the empirical p.m. Since in some sense P is close to P when n is large, n ¿ ¿ LLd. from P and builds the empirical p.m. if one samples Xl ' . , Xm n n -1 mn ¿ ¿ P T(P ) conditionally on := mn l: i =1 a ¿ ' then the behaviour of P m n,m n n n X. 1 T(P ) should imitate that of when n and mn get large. n This idea has lead to considerable investigations to see when it is correct, and when it is not. When it is not, one looks if there is any way to adapt it.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 244 pp. Englisch.
